Webinar Recording: How After-Hours Patient Calls Reveal Opportunities to Improve Care Quality

Most home health and hospice organizations are already collecting after-hours triage data. Very few are using it as a quality improvement tool.

In this webinar, Patrick O'Brien, RN, MSN, and Kelly Stanley, BS, RN, walk through how after-hours call patterns can surface care delivery gaps, drive structured process improvement, and reduce the kinds of preventable calls that strain on-call staff and put patients at risk.

The conversation covers real data examples, including medication refill volume trends and call timing heat maps, and connects those signals directly to the PDSA cycle and QAPI program design. Whether you're just starting to build out your QAPI program or looking to add a new data source to an existing one, this recording gives you a practical framework you can apply immediately.

In This Recording, You'll Learn:

• How to distinguish avoidable from unavoidable after-hours calls and what each type signals about care quality
• Why medication refill calls spike on weekends and what that pattern tells you about weekday visit processes
• How to read escalation rate data as a standalone quality signal
• A step-by-step audit framework for identifying root causes before opening a PIP
• How to scope a PIP to stay manageable and show measurable progress within 30 to 60 days
• How to sustain improvements after the PIP closes by assigning processes to positions, not people

This session explores how greater visibility into after-hours patient needs can help organizations move from reactive response to proactive improvement.

WEBINAR TRANSCRIPT:

Ellen Kuebrich 

Welcome everyone to the webinar. I'm Ellen Kuebrich, the Chief Strategy Officer here at CareXM, and I'll be your moderator today.

Before we get into the introductions of our two speakers, I want to start with a question for our audience to think about. How many of you have a QAPI program that includes after-hours call data as a standard data source?

I'll give you a second to think about it, because in our experience working with home health and hospice organizations across the country, the answer to that question is almost always "not yet." And more often than not, that's not a problem. It's actually the whole reason that we're here today.

You already know QAPI. You know the mandate. You're doing the PDSA cycle, you're doing PIPs. What we're going to show you today is a data source that most organizations are sitting on but not fully utilizing. And it's one that's generating a continuous signal about care quality every single night.

After-hours triage data captures what your patients and their caregivers are experiencing between visits. The moments when the office is closed, something isn't right, and they make a call. And most organizations treat that as a call management function. We log it, we resolve it, and we move on.

What Kelly and Patrick are going to show you today is that those calls are actually a really valuable quality feed. The patterns in that data, what patients are calling about, when they're calling, when those calls are spiking, how often nurses have to escalate, those patterns tend to point directly at process gaps that are happening during business hours. And more importantly, they're pointing to the kind of structured improvement work that your QAPI program is designed to address.

So with that, I want to introduce our two speakers. First, I'm pleased to introduce Patrick O'Brien. Patrick O'Brien, RN MSN, is a nurse leader with more than 15 years of progressive leadership experience in home health and hospitals. Throughout his career he has partnered with organizations ranging from startup programs to large multi-state operators, helping teams build sustainable quality infrastructures that improve both patient outcomes and organizational performance. Patrick comes to us today with deep expertise in clinical operations, staff development, performance improvement, and QAPI program design, with a particular passion for helping organizations translate data into meaningful action.

Joining Patrick is Kelly Stanley, BSN RN, Director of the Clinical Solutions Group here at CareXM. Kelly brings a unique blend of frontline hospice and home health experience paired with provider-side leadership and healthcare technology expertise. Throughout her career she has helped post-acute organizations improve care coordination, operational performance, and patient outcomes through smarter use of clinical and operational data. And today she's going to lead us down the path of showing us how after-hours triage data can move beyond call management and become a powerful driver of quality improvement.

So it looks like what we have today is a triage expert and a quality expert in the same room, which is either a perfect combination for this webinar or the setup to a very niche joke. Either way, I think you're going to leave with something you can actually put to use in your organization tomorrow. Patrick, Kelly, welcome. Thank you both for being here.

Patrick O'Brien

Wonderful. Thank you so much, Ellen. Thanks everybody for being here.

I think it's very easy, and it's certainly something I have personally been guilty of, to think about after-hours triage as purely an operational convenience. And certainly it is, but that really limits us. Because what I now know to be true is that after-hours triage is generating a continuous stream of patient data during the hours the office is closed, as Ellen said. And those tend to be the exact hours when patients and caregivers are most likely to surface unmet needs we might not yet be aware of.

So the data we're aggregating doesn't just log volume. It also gives us great insight into what patients are really experiencing between visits, whether that's pain levels, gaps in medication, or just uncertainty about what they should do next.

And that signal operates at two distinct levels. The first is at the individual patient level, because if we're getting repeated calls from a particular patient, that gives us clear insight into what that individual patient and their caregiver might be experiencing. But on a broader level, we can identify patterns, whether by call type, call timing, or escalation rate. Those can give us good insight into where there might be gaps in care delivery and real opportunities for process improvement.

Patrick O'Brien

Not all calls give us the same type of insight. We tend to think of them as either unavoidable or avoidable, and those send us in very different directions.

When I talk about unavoidable calls, I generally mean those that are clinically appropriate. A good example is a home health patient with CHF. He's taking all of his medications as prescribed, restricting his sodium intake, doing daily weights. But on a Saturday evening he notices that his ankles are swollen, and so he does exactly what we've instructed him to do. He calls the care team because he wants to get ahead of it before it ends up in another hospitalization. That's an example of a call we absolutely want to get after hours. That is clinically appropriate.

The other end of the spectrum are avoidable calls, and those are the ones that might indicate a process gap or a communication failure. Think about a medication refill needed on a weekend, or someone calling on Friday night to ask if their clinician is coming the following day. Things we might have gotten ahead of during normal business hours.

Distinguishing between the two is part of what helps us identify where we have quality improvement opportunities. And we can leverage that data in two different directions. We can use it retrospectively, when we know we have a quality issue and want to back into context for a root cause analysis. Not just what went wrong, but what the early signs were, what those leading indicators might have been. And we can also use it prospectively, identifying patterns in volume and call type so they surface an early warning signal before the quality problem shows up downstream.

Patrick O'Brien

So Kelly, let me ask you a question before we get into the data. I think a lot of organizations think of after hours as kind of a black box. They may not have a lot of data, or at least not data that's giving them a deep analysis of who was calling and what the reason was. A lot of times calls go in, nurses respond, and they document in the medical record. And then when the office opens Monday morning, maybe we take a cursory look at what happened in the after hours. But maybe we don't really know what to look for. So what would you look for in after-hours call volume?

Kelly Stanley

Yes, absolutely. And I think that's so true. We really think about our patients within the construct of visits because that's how we deliver care, but they're living this whole life between those visits. And we actually have the ability to capture some of that data in the after-hours triage, because if we're really lucky, maybe some of that context lives in a narrative note or some sort of unstructured place within the medical record. But it's really difficult to capture that information and make it actionable.

So breaking down calls by call type is really where a lot of that value starts to emerge. Aggregate volume is going to tell you kind of how busy your after-hours program is, or how many calls you're getting. When we break it down by call code, we start to understand why those calls are coming in, and that's where the quality signal really starts to emerge. Different call types point to different upstream breakdowns and improvement opportunities. That's where we start to move from thinking about this data as a utilization report and more toward a quality tool.

Patrick O'Brien

Based on what you said, the calls that you really do want coming in after hours are those status change and symptom management calls. If we look at something like general communication or medication, those seem to be the ones indicating opportunity for improvement. Is that right?

Kelly Stanley

Yes, absolutely. Medications is a great example of that, specifically medication refills. That's something we see when clients come on board and we start building that data. The number, both as a raw volume and as an overall proportion of calls coming in, is always very surprising to clients. And I think that surprise is meaningful, because it signals that the data we're collecting after hours is something they can't necessarily get from their existing reporting.

The reason medication refills matter so much is that, almost by definition, prescriptions follow a pretty predictable timeline. These calls should not routinely be landing in the after hours. They typically represent some kind of upstream breakdown in process, whether that's in handoffs or even in patient education.

We see about 3 to 4% of after-hours calls are medication refills. That might not sound like a compelling number, but over the last five quarters that actually represents a volume of 122,000 calls. That's 122,000 needs that probably could have been proactively managed during business hours but instead spilled over into the after hours.

The implications go beyond basic operations when we're specifically talking about medication refills. A patient waiting after hours for a pain medication refill that should have been handled during the day isn't really just a logistical problem. It's a quality problem with real consequences for clinical outcomes, caregiver experience, and satisfaction scores down the road.

Kelly Stanley

Knowing how many calls are coming in tells you there's potentially a problem. Knowing when they're coming in starts to tell you where that problem may be located.

When we look at call timing data, a heat map breaking down call volume by day of the week and time of day, we start to see patterns that point directly upstream to specific process gaps. The timing of a call is often just as diagnostically significant as the call type itself.

With medication refills specifically, what we find almost consistently across clients is that Saturday and Sunday account for about half of all medication refill call volume. That's a pretty disproportionate concentration on those weekend days, and it's extremely actionable.

When we see calls clustering on Friday evening and over the weekend, that really points to gaps in how medication supply is being monitored during weekday visits. Whether that's inconsistent tuck-in calls, insufficient medication review during weekday visits, or a patient education issue, something is not landing or functioning as intended.

Conversely, if we see a spike in those calls in the first few days after a patient is admitted, that's going to point us more upstream toward the admission process. That could be patient education, something with the pharmacy partnership, how we deploy comfort kits, or how we're communicating with physicians and managing standard order sets. We've got an opportunity there if we're seeing those calls cluster right at the beginning.

And then at the other end of the spectrum, we see calls concentrated in the final days of life as well. That might point toward conversations we're having at IDT and whether we're recognizing that a patient is declining early enough. Are we prescribing as proactively as we might when we see patients declining? Wherever that heat map is pointing us, it doesn't necessarily give us all the answers, but it gives us a really good idea of where to start looking. And in each of these scenarios, it's pointing to something we could be doing during business hours before it becomes an after-hours crisis.

Kelly Stanley

Escalation is a really helpful third dimension. It gives us a lot of context about how complex those calls are when they're coming into the triage team. In triage parlance, an escalation is when the triage nurse serving a call is not able to fully resolve the caller's concern and has to loop in the on-call staff for next steps. Think about it as the difference between a call that's handled right there in the moment and a call that triggers a chain of care coordination in the after hours. That may mean waking up clinicians, contacting a physician after hours, or dispatching a nurse for an unplanned visit.

The escalation rate is really meaningful because it's a quality signal all on its own. A high escalation rate across call types can tell us that patients are reaching out after hours in a state of unmet need that goes beyond what a triage nurse can resolve, which points to a gap in that daytime care and preparation.

Back to the medication refill example specifically, we see that about 40 to 50% of calls that come in with that call code have to be escalated. Nearly half. When a triage nurse can't resolve a refill call, it typically means a straightforward pharmacy contact isn't going to be what resolves the call. When it escalates, it's often because an order is required. And when an order is required after hours, there's a really high likelihood, and the data substantiates this, that it has to do with a controlled substance, which very often means a comfort medication. Opioids, anxiolytics, antiemetics, comfort medications that patients and their caregivers are truly counting on.

That's a really significant distinction, because a comfort medication escalation in the middle of the night means a patient is to some degree suffering in some capacity, whether they're waiting for pain relief or anxiety relief. And that is a supply failure that probably should have been anticipated and resolved proactively rather than in real time after hours. Each one of those escalations represents a moment that could have and should have been prevented upstream.

Kelly Stanley

It's very helpful to think about medication refill data through an operational lens. But looking at it only through that lens leaves a lot of the value of this data on the table, because you don't have to pull on that thread very hard to see that there are significant clinical implications that come into focus pretty quickly.

Specifically when we're talking about hospice patients, so much of what they're relying on their provider for is symptom management as they move through the process. When you think about what this really looks like when it fails after hours, this is a caregiver whose loved one is experiencing uncontrolled pain or who is becoming agitated. They go to administer the medication as they've been instructed to do, and they come up empty. It isn't there. And potentially this is the middle of the night. This is a frightening experience. It can feel very isolating. And foundationally, it's antithetical to the whole value of hospice and what we're really trying to provide for patients.

Worst case scenario, this ends up in a hospitalization if the patient or caregiver panics and can't get the symptoms under control. Maybe that ends up looking like a burdensome transition, hitting a quality metric. Or at the very least, this probably becomes something of a defining memory of that family's hospice experience. And it doesn't stay in that moment. We know it ends up showing up in CAHPS scores later, whether that's in timeliness of help, how effectively the organization managed pain and symptoms, or how we communicated with the family.

So that after-hours information is quietly generating the conditions for those survey responses later, whether we're paying attention in the moment or not. It's not just telling us where the process broke down. It's telling us that a patient might have suffered and the family is going to carry that with them as they think about their experience.

Ellen Kuebrich

So we're talking about medication refills, yes, but we're also talking about a signal. The calls are telling us about something going wrong, as you said, whether it's admissions, education, medication management, communication, anticipatory prescribing. Something's not working the way we intended. The data doesn't tell us what went wrong, but it does tell us where to look. And that's where QAPI takes over.

So Patrick, let's assume we are seeing a hospice with this kind of pattern. How do you take this data, this signal, and do something with it that's meaningful? How do you figure out where that gap is?

Patrick O'Brien

Yeah, thanks Ellen, and thanks Kelly. So we know there's a broad problem. We know there's an increase in volume in these after-hours calls specifically as it relates to medication. But that's just one part of the story. Kelly has done a really nice job of painting a picture of all the different potential pathways that could lead up to a medication not being there for a patient. Now our responsibility is to figure out why. So we become detectives.

To become a detective of our after-hours calls, we need to build out audits. Our audits are going to be our first line of defense when we want to address these after-hours calls. That means looking at all the different components: the administrative component, the operational component, the clinical component, and the patient satisfaction component.

The first thing I see when building out audits is that a lot of administrators will look at a problem and say, "Oh, it's our clinicians. They just aren't doing the refills on the visit." But I really urge people to slow down and take a look at all of it when you're building out your audit tool. You should address all of the different things that possibly could be leading to a medication not being there for a patient. Maybe it was delayed because a physician didn't sign a controlled substance order timely. Maybe you used mail order for your pharmacy and there was a mailing delay.

So as you're building your audit tool, look at it from your clinical lens, your administrative operations lens, and also the patient satisfaction lens.

Patrick O'Brien

Then we build our questions to reveal our answers. I look at an audit tool as a decision tree. Maybe I start with a question as simple as: was this medication refill avoidable? If yes, we move into the clinical components. Is there documentation evidence that the nurse documented a medication reconciliation? Was there a medication countdown on the last visit? If both of those are yes, then we move into an operational standpoint. Is there evidence this medication was refilled timely with the pharmacy? If yes, then we go to logistics. We go to the delivery service. That's where we find our breakdown.

The breakdown for this patient lived with a delivery that was supposed to be two days but turned into three. Nothing to do with our clinician, nothing to do with our pharmacy. And as we all know, when you're waiting on a two-day delivery, sometimes it doesn't come in two days. With medications, especially when we're trying to manage symptoms, timeliness really matters. So when building these tools to reveal answers, it's important to cover multiple areas of where breakdowns could occur.

Patrick O'Brien

Step three is letting the data do the talking. You may be surprised at where your data guides you. I'm not asking anyone to audit 122,000 calls. What I'm saying is you could take a sample of your after-hours calls and start building trends from that. Even after auditing 15 to 20 calls, you can start seeing patterns emerging that tell you where to focus your improvement efforts. So you're not guessing anymore. It's not your intuition. It's not the new nurse. It's the actual data that's driving what you're doing.

Usually within a couple of weeks and a handful of audits, you should be able to establish some patterns about what's happening.

Patrick O'Brien

Now we turn what we find into a plan that actually gets executed. We're talking about the PIP, our process improvement project. The PDSA: Plan, Do, Study, Act.

A pitfall I see in agencies is that they complete their audits, find maybe 5 or 10 things with some deficiency, and then try to address all of them in one big PIP. What happens is the problem statement becomes really broad, you have 25 different interventions, and the team is completely overwhelmed before they even get started. Nothing gets done well because you're running 25 interventions for one PIP.

My recommendation is to pick your highest risk findings. Write a clear problem statement and measure one or two goals. Make it achievable. Give yourself 30 to 60 days and start there.

For this medication refill example, maybe there is no documented evidence of refill assessment during the skilled nursing visit. That's very specific. It's very fixable, and you could often see improvement in as little as 30 days. So we have our intervention, we have our goal, we have a clear problem statement. Then we take our plan and turn it into what we're going to do.

Our interventions become tasks. We are going to create education materials. We are going to host education sessions. We are going to review clinical documentation for evidence of that medication refill documentation. It's a really simple and achievable goal. And just as a caveat when building out all the things you're going to do: be mindful of scope. If you build out 15 tasks for each intervention, your PIP gets bigger than you and you can't achieve the goal. For each intervention, pick three tasks that are going to get you the biggest return. You can always add more tasks and more interventions later in the life of the PIP.

Patrick O'Brien

Now we move from the Do stage into the Study stage. This is where we start tracking our wins. I'm a big believer in small wins. Nothing feels better than completing that first intervention. We planned to educate. We got our training material developed. We held our education sessions. The team feels good. We're already seeing improvement in the documentation. That's the Study phase. We can mark that intervention complete. We may not be at the end of our PIP, but for that intervention, we've hit our goal. And we can now start seeing some improvement in after-hours call volume.

It might not be the biggest shift in call volume, but we know we've completed the most essential part of this plan, which was getting the education material out to the right people.

Patrick O'Brien

Then we move into the Act stage. This is where we document what went well during our PIP, what needed improvement, which interventions hit goal, and which ones didn't. Not every intervention is going to have the same weight. Kelly mentioned tuck-in visits earlier. If you implement a tuck-in call for your patients and start seeing a reduction in after-hours refill volume, that call would probably carry more weight in hitting the goal versus some of the education work, because you have another safety point where you're catching medications that need to be refilled more timely.

So as you have that small win with the education intervention, don't be surprised if call volume doesn't drop dramatically. But maybe once you implement the tuck-in call, that's when you really see that next quarter where volume drops.

Once you've hit your goal, make sure you finalize this process into your workflow. Sometimes we improve a problem and then forget to work it into our standards of operations. That might mean building it into a policy or creating a standard workflow. For example, that tuck-in call or weekend check-in call. Maybe it doesn't live with Nancy or Rebecca. Maybe it lives with a position.

I worked at an agency where we had Nancy, and that's why I use Nancy. Nancy was the one who always did the calls on Friday. Patients loved Nancy. Caregivers loved Nancy. The amount of medication refills Nancy was able to process and supply needs she was able to address was pretty tremendous for a census of a couple hundred patients. Families came to look forward to her call, and it saved the weekend and after-hours staff a lot of additional calls.

As much as we love Nancy, make sure that if it's the office manager role that's Nancy, that process lives with the position. That way you can keep the momentum going after the PIP closes.

Patrick O'Brien

Once you fix your PIP, the question is how to keep it fixed. Make sure processes live with positions, not always specific staff members. Make sure that if a policy needs to be updated because of a PIP improvement, it gets updated. You want to maintain the progress you've made.

And keep an eye on what's happening. Just because we've reduced after-hours call volume with our PIP doesn't mean we stop looking. Set thresholds for what's acceptable and what's not. We're not saying no call should exist. We're saying let's reduce the calls that create unnecessary work so we can really provide excellent care. In a way, you can relate the reduction in after-hours medication calls to increased quality overall, because your resources now have more time to take care of patients who are more critically ill and need their attention.

Make sure that after the PIP is closed, you keep an eye on after-hours events. Sometimes the volume does go back up, but you start the process over. Maybe this time it was a clinical intervention being missed, but next time it's operational. Maybe you have a pharmacy partner that's struggling to meet your needs. This is a very fluid cycle. It can start, it can stop, and it can restart again if needed.

Ellen Kuebrich

I want to keep coming back to the fact that the entire conversation really started with a phone call. A patient or caregiver had a need that shouldn't have been unmet in the after hours. And we've just walked from that unplanned interaction all the way through a structured quality improvement cycle that ended with a better process and a better experience. And with some critical thinking, it truly does improve the patient experience, which I know is why we're all here. That's the full loop. And the fact that it's starting with data you're probably already sitting on is the part that really stood out to me. Patrick and Kelly, thank you so much. Do you have any closing thoughts before we open it up to questions?

Patrick O'Brien

The only thing I'll say as a closing thought is there's nothing too small to be a process improvement project. A lot of times I see agencies who proactively fix problems and don't document them as PIPs because they feel like nurses, we're nurses by background. Kelly's a nurse by background. A lot of times we just want to fix things. We see a problem, we fix a problem, but we don't document the five great things we did to fix that problem. Give yourself credit for the good work you're doing. Even if a PIP feels automatic, put it on paper. Take the credit.

Kelly Stanley

And I would just echo what Patrick said. These are not boxes you check and move along. This is a continuous improvement effort. As you move forward, you learn a little bit and do a little bit better, but new problems arise. Just continuing to iterate on that cycle, put new interventions in place, and improve practice a little bit at a time.

Audience Q&A